1. Field of the Invention
The present invention relates to a navigation system which is installed in a mobile object so as to detect at least one of the position and the traveling azimuth thereof.
2. Description of the Related Art
Known navigation systems for mobile objects include a radio navigation system wherein the position of the mobile object is directly determined using a radio wave signal sent from, e. g., a GPS (GLOBAL POSITIONING SYSTEM) satellite or a radio beacon, and an inertial navigation system wherein the traveling azimuth and movement distance of the mobile object are measured so as to find the position thereof on the basis of the measured values. There has also been known a navigation system wherein both the radio navigation system and the inertial navigation system are combined, and wherein they are changed-over depending upon circumstances. A navigation system which is endowed with the function of receiving a signal from a geostationary satellite, in addition to the signal from the GPS satellite revolving round the earth, has also been studied in order to enhance the performance of navigation.
The radio navigation system equipped with a GPS receiver which the radio wave signal from the GPS satellite (hereinbelow, this signal shall be called the "GPS signal") so as to obtain an absolute position of the mobile object. The GPS receiver detects a range (a pseudo range), a range rate (the change rate of the pseudo range) and information on the GPS satellite itself by receiving the GPS signal. Further, when the GPS receiver is capable of receiving GPS signals from four or more GPS satellites, it can calculate the absolute position of the mobile object uniquely on the basis of the received signals.
In the system having the radio navigation system and the inertial navigation system in combination, the absolute position obtained as stated above is commonly utilized for correcting the measurement error of the inertial navigation system. In an urban district, etc., however, the signals from the four GPS satellites are often unreceivable due to topography, buildings, etc. It is accordingly difficult to obtain the absolute position at all times.
An example of the inertial navigation system in the prior art includes a gyro sensor and a geomagnetism sensor employed as an azimuth sensor; and output values from both the sensors are passed through a filter, whereby an azimuth of high accuracy is obtained (Official Gazette of Japanese Patent Applications Laid-open No. 219610/1989 and No. 188316/1991).
In the example disclosed in the official gazette of Japanese Patent Application Laid-open No. 219610/1989, the filter is utilized for increasing the proportion of use of the gyro sensor when the precision of the gyro sensor is high, and for increasing the proportion of use of the geomagnetism sensor when the precision of the geomagnetism sensor is high. The proportions at which the individual sensors are used, are determined from the empirical statistical distributions of the errors of the respective sensors. On the other hand, in the example disclosed in the official gazette of Japanese Patent Application Laid-open No. 188316/1991, the filter employed is a Kalman filter, and a covariance matrix of error (noise) components of individual sensors are computed from measured values of the respective sensors, whereupon the property variations of the noise components of the respective sensors are considered.
Besides, in a case where signal from geostationary satellite is directly received by an antenna attached to a mobile object, it is important to control the attitude of the antenna normally toward the geostationary satellite in accordance with the turning of the mobile object. In this regard, a prior-art example is a navigation system as disclosed in the official gazette of Japanese Patent Application Laid-open No. 204168/1992, in which a turning angle sensor for detecting the azimuthal change of the mobile object is mounted and which has the antenna attitude control function of directing the antenna toward the geostationary satellite by the use of the turning angle sensor.
The prior-art examples, however, need to heighten the sensor precisions or to install a plurality of sensors for the purpose of enhancing the accuracy of the positioning (i. e., the determination of the position) of the mobile object, resulting in an increase of the cost of the navigation system.
In view of the above drawback, the present invention is intended to provide a navigation system which can efficiently enhance the positioning accuracy without employing any sensor of high precision. Concretely, it is intended to deal with the following five issues:
The first issue pertains to a navigation system equipped with a GPS receiver for receiving signals from GPS satellites.
In such a navigation system, when the signals from the four GPS satellites are receivable, pseudo ranges from the respective satellites to the GPS receiver and the change rates thereof ("ranges" and "range rates") are measured, and the absolute position of the GPS receiver, namely, the absolute position of a mobile object carrying the navigation system thereon, can be uniquely obtained from the ranges as well as the range rates and the positional information items of the respective satellites transmitted from these satellites.
However, where such a navigation system is installed in the mobile object which moves on the ground, the signal from the GPS satellite is interrupted by mountains or buildings in a mountainous district or an urban district. This leads to the problem that, although the ranges and the range rates concerning at most three of the GPS satellites can be measured, the signals from the four GPS satellites cannot be simultaneously received, so that position detection often becomes impossible.
The second issue pertains to a navigation system in which a plurality of sensors such as a GPS receiver, a gyro sensor, a car velocity sensor and a geomagnetism sensor are used.
Such a navigation system equipped with the plurality of sensors has the problem that errors involved in the respective sensors cause degradation in the accuracy of the system. As another problem, notwithstanding that the outputs of the sensors sometimes contain information items which are duplicated with respect to each other, such information items are not always utilized.
The third issue pertains to an azimuth sensor normally included in a navigation system.
Usually, the azimuth sensor consists of a gyro sensor and a geomagnetism sensor. Since the gyro sensor is an angular velocity sensor, the output signal thereof must be integrated in order to find an azimuth. Therefore, when a bias error involved in the measured value of the gyro sensor exists and increases with time, a large azimuthal error results.
On the other hand, in a geomagnetism sensor, errors develop due to an offset magnetization effect and the .mu. (mu) effect when that constituent member of a mobile object to which this sensor is attached is made of a magnetic material. Herein, the "offset magnetization effect" is the phenomenon in which the constituent member is magnetized. The ".mu. effect" is the phenomenon that, when the shape of the constituent member of the magnetic material surrounding the geomagnetism sensor is asymmetric, the error is caused in the geomagnetism sensor by the asymmetry. The factors of these errors are not considered in the prior-art techniques mentioned above (Official Gazettes of Japanese Patent Applications Laid-open No. 219610/1989 and No. 188316/1991). The prior art therefore has the problem that, when both the errors are large, a satisfactory accuracy is not attained in the measurement of the azimuth.
The fourth issue pertains to the attitude control of a signal receiving antenna which is employed in a radio navigation system or the like.
By way of example, a signal required for positioning based on the radio navigation is normally received at a high sensitivity by controlling the attitude of the antenna, so that the performance of the navigation can be enhanced. Heretofore, the azimuthal change of a mobile object itself has been detected independently of navigation processing, and it has been utilized for the attitude control. It is obvious, however, that the attitude control of the antenna can be similarly carried out by utilizing the azimuth or position of the mobile object obtained by the navigation processing, and the position of a satellite which sends the signal to-be-received and whose position is known beforehand. Nevertheless, these information items are not utilized, which incurs the problem that redundant parts are present in the architecture of the system.
The fifth issue pertains to an azimuth sensor included in a navigation system, likewise to the third issue stated above. In particular, it pertains to error characteristics peculiar to a geomagnetism sensor and a gyro sensor which constitute the azimuth sensor.
The geomagnetism sensor generates noise for a short term in an environment of disturbed magnetic-field which is affected by a high-voltage cable, a building, etc., but it produces comparatively correct azimuths over a long term. In contrast, the gyro sensor is not susceptible to a magnetic-field environment at all and produces correct relative azimuthal changes for a short term, but it cumulates azimuthal errors with the lapse of time due to a drift (fluctuation in an angular velocity bias) over a long term.
With the intention of solving such a drawback, by way of example, a method wherein sensor signals are subjected to a filtering process is employed in the example disclosed in the official gazette of Japanese Patent Application Laid-open No. 219610/1989. More specifically, the situation of the magnetic-field environment is detected from the difference between the amounts of azimuthal changes of the geomagnetism sensor and the gyro sensor every unit time, and the value of a filter gain is regulated in accordance with the detected situation in order to bring a filter output nearer to an azimuth detected by the geomagnetism sensor (hereinbelow, this azimuth shall be called the "geomagnetic azimuth").
A similar method is taught by the example disclosed in the official gazette of Japanese Patent Application Laid-open No. 188316/1991 wherein a Kalman filter process is introduced for calculating the filter gain. In this prior-art technique, the noise components of the geomagnetism sensor and the gyro sensor are determined from, for example, the variance values of the azimuthal data of the respective sensors in the straight traveling mode of a mobile object. Thereafter, the filter gain which is weighted with respect to an azimuth determined by the sensor of less noise is calculated on the basis of the values of the noise components in accordance with a Kalman filter algorithm.
Qualitatively, both these prior-art techniques adopt a method wherein, on the basis of the characteristics of the respective constituent sensors of the azimuth sensor, the gyro sensor is weighted for the short term, and the geomagnetism sensor is gradually weighted more over the long term. Additionally, the former technique determines the rate of convergence on the geomagnetic azimuth (the filter gain) from the difference between the amounts of the azimuthal changes of both the sensors, while the latter technique determines it from the variance values of the data of both the sensors in the straight traveling mode. That is, the rate at which the filter output is converged on the geomagnetic azimuth is determined from only the output data of the geomagnetism sensor and the gyro sensor.
In the navigation system, however, the rate of convergence on the geomagnetic azimuth is closely relevant to car velocity data. More specifically, in the case where the convergence on the geomagnetic azimuth in a navigation system in which a traveling position is calculated on occasion from an estimated azimuth and a traveling distance obtained by integrating a car velocity, the convergence with respect to the traveling distance ought to be considered, not the convergence with respect to the lapse of time. As the car velocity is higher, thus further increasing the traveling distance, an accurate traveling azimuth is required more quickly.
In this regard, the prior-art examples have the problem that, as an extreme example, even in both a case where the vehicle as the mobile object is at a standstill, that is, where an azimuthal error does not lead to a positional error, and a case where the vehicle is traveling at a high velocity, that is, where even a slight azimuthal error leads to a large positional error, the rate of the convergence on the geomagnetic azimuth is kept identical as long as the noise characteristics of the geomagnetism sensor and the gyro sensor remain unchanged.
Moreover, in the former prior-art example explained above, the method of calculating the filter gain from the difference between the amounts of the azimuthal changes of both the sensors is not a precise method, and the occurrence of an azimuthal error attributable to this fact is inevitable.
On the other hand, in the latter prior-art example, the Kalman filter algorithm is adopted as a reasonable frame for determining the filter gain. A chance for altering the filter gain, however, is limited only to an occasion where the statistical process has been permitted by collecting the data in the straight traveling mode. That is, the filter gain is determined at a very low frequency and it can not really be called a "real-time value". Conversely, the use of an inappropriate filter gain is continued until an appropriate filter gain has been determined owing to the permitted statistical process. This incurs the problem that the position detecting precision of the navigation system worsens.
Another problem lies in the method of the statistical process for estimating the sensor noise. Some components of the sensor noise are peculiar to the respective sensors. By way of example, offset magnetization noise is involved in the geomagnetism sensor, and it can develop into a large offset error in the sensor output in a moment. In the case of the gyro sensor, unidirectional azimuthal errors cumulate gradually.
Further, in either of the prior-art examples, the corresponding one of these noise components is not modeled at all. In the prior art, the very azimuthal data items delivered from the sensor are statistically processed to calculate the variance values, from which the filter gain is obtained. With this method, in the case where the noise peculiar to each sensor as stated above has occurred, it cannot be properly dealt with. As a result, it might even be the cause of developing a large azimuthal error.
In the above, the drawbacks of the prior-art examples in the filter processes applied to the estimation of the azimuth have been described. The fifth issue, however, is not restricted to the azimuth estimation. It is a common issue even in a case where a certain specified physical quantity relevant to navigation processing is similarly estimated using outputs from sensors, for example, a case where the position of the mobile object is estimated.